An Efficient Gray-level Clustering Algorithm for Image Segmentation

Gray-level clustering is an important procedure in image processing, which reduces the gray-level of an image. In order to display an image with high gray level in a screen with lower gray level, a good gray-level clustering algorithm is necessary to complete this job. Based on the mean value and standard deviation of histogram within a sub-interval, a novel recursive algorithm for solving the gray-level reduction is proposed in this paper. It divides the sub-interval recursively until the difference between original image and clustered image within a given threshold. Experiments are carried out for some samples with high gray level to demonstrate the computational advantage of the proposed method.